Advanced FastAPI

We continue using FastAPI in this module with a look at more complex endpoints and data retrieval functions for our REST API. After going through this module, students should be able to:

Identify valid and invalid FastAPI route return types
Use both Python built-in types (e.g. int) and Pydantic data models to valid FastAPI inputs and return types
Extract Content-Type and other headers from FastAPI route responses
Add query parameters to GET requests, and extract their values inside FastAPI routes
Deal with errors from user-supplied input to an API and handle Python exceptions
Handle multiple request methods to support CRUD operations

Note

We will continue to work on the the individual student VMs. Like last time, it will be helpful for you to have two SSH terminals open to your VM at the same time so you can run your FastAPI application in one terminal and test it in the other.

Defining the URLs of Our API

One of our first goals for our API will be to provide an interface to a dataset. Since the URLs in a REST API are defined by the “nouns” or collections of the application domain, we can use a noun that represents our data.

For example, suppose we have the following dataset that represents the number of students earning an undergraduate degree for a given year:

def get_data():
    return [ {'id': 0, 'year': 1990, 'degrees': 5818},
             {'id': 1, 'year': 1991, 'degrees': 5725},
             {'id': 2, 'year': 1992, 'degrees': 6005},
             {'id': 3, 'year': 1993, 'degrees': 6123},
             {'id': 4, 'year': 1994, 'degrees': 6096} ]

In this case, one collection described by the data is “degrees”. So, let’s define a route, /degrees, that by default returns all of the data points.

EXERCISE 1

Create a new file, degrees_api.py to hold a FastAPI application then do the following:

Import the FastAPI class and instantiate a FastAPI application object.
Copy the get_data() method above into the application script.
Add a route (/degrees) which responds to the HTTP GET request and returns the complete list of data returned by get_data().

In a separate Terminal use curl to test out your new route. Does it work as expected?

Tip

Refer back to the Intro to FastAPI material if you need help remembering the boiler-plate code.

EXERCISE 2

Back inside the degrees_api.py file, let’s add a second route, /degrees/{id} that returns the data associated with a single dictionary. There are often design questions one should consider when writing new code. In this case, we have:

What method(s) should it accept?

What type will the incoming id field be from the user?

How will you find the corresponding dictionary?

What should happen if the user enters an id that doesn’t exist?

Discussion

By default, FastAPI uses String for the types of path variables. If we use a route declaration like this,

@app.get('/degrees/{id}')
def degrees_for_id(id):
    # implementation...

Then any GET request with a URL path that starts with /degrees/ and ends with any string will match. That is,

/degress/0 –> id holds the value "0" as a Python String.

/degrees/A –> id holds the value "A" as a Python String.

/degrees/one –> id holds the value "one" as a Python String.

will all match the degrees_for_id route and the variable, id will hold a str value. In this case, we’ll have to deal with the str type in our function, converting it to int, etc.

Typed URL Parameters

We can specify the types of the URL parameters we are expecting using the syntax <variable_name:type>. For example, we could change our degrees_for_id route declaration as follows, to indicate we required the id variable to be an integer:

@app.get('/degrees/{id}')
def degrees_for_id(id: int):
    # implementation...

With the above definition, a request like GET /degrees/A will no longer match our degrees_for_id route while a request like GET /degrees/2 will call degrees_for_id with an integer type for the id variable.

EXERCISE 3

Modify your degrees_for_id route to specify an integer path parameter.

Responses in FastAPI

Suppose we wanted to add a third route that just returns a single value, the number of degrees associated with a particular dictionary. We might proceed as follows:

For the URL path, use /degrees/{id}/degrees

Iterate through the list looking for the dictionary with the same id as the input.

If we find a dictionary, d, with the same id, return d['degrees'].

Let’s try that and see what happens.

EXERCISE 4

Implement a new route for the /degrees/{id}/degrees endpoint.

EXERCISE 5

With your API server running in one window, open a Python interactive session in another window and:

Make a GET request to your /degrees URL and capture the response in a variable, say r
Verify that r.status_code is what you expect (what do you expect it to be?)
Verify that r.content is what you expect.
Use r.json() to decode the response and compare the type to that of r.content.

Then, repeat the above with the /degrees/<id>/degrees endpoint.

Note

What Python package will you need to import to make the HTTP request?

HTTP Content Type Headers

Requests and responses have headers which describe additional metadata about them. Headers are key:value pairs (much like dictionary entries). The key is called the header name and the value is the header value.

There are many pre-defined headers for common metadata such as specifying the size of the message (Content-Length), the domain the server is listening on (Host), and the type of content included in the message (Content-Type).

We can use curl or the Python requests library to see all of the headers returned on a response from our FastAPI server. Let’s try it.

EXERCISE 6

Use curl to make a GET request to your /degrees endpoint and pass the -v (for “verbose”) option. This will show you additional information, including the headers. Note that with -v, curl shows headers on both the request and the response. Request headers are lines that start with a > while response headers are lines that start with a <.
Use curl again to make the same request, but this time pass the --head option instead of the -v; this will show you only the headers being returned in the response.
Inside a Python shell, use requests to make the same GET request to your /degrees endpoint, and capture the result in a variable, r. Inspect the r.headers attribute. What is the type of r.headers?

[coe332-vm]$ url -v 127.0.0.1:8000/degrees
*   Trying 127.0.0.1:8000...
* Connected to 127.0.0.1 (127.0.0.1) port 8000
> GET /degrees HTTP/1.1
> Host: 127.0.0.1:8000
> User-Agent: curl/8.5.0
> Accept: */*
>
< HTTP/1.1 200 OK
< date: Wed, 11 Feb 2026 22:30:49 GMT
< server: uvicorn
< content-length: 181
< content-type: application/json
<
* Connection #0 to host 127.0.0.1 left intact
[{"id":0,"year":1990,"degrees":5818},
{"id":1,"year":1991,"degrees":5725},
{"id":2,"year":1992,"degrees":6005},
{"id":3,"year":1993,"degrees":6123},
{"id":4,"year":1994,"degrees":6096}]

>>> import requests
>>>
>>> response = requests.get('http://127.0.0.1:5000/degrees')
>>>
>>> response.headers
{'date': 'Wed, 11 Feb 2026 22:32:55 GMT',
'server': 'uvicorn',
'content-length': '25',
'content-type': 'application/json'}

We see that we are sending a Content-Type of 'application/json', which is what we want. That is how the Python requests library is able to provide the r.json() function to automatically convert to a Python list or dictionary.

Media Type (or Mime Type)

The allowed values for the Content-Type header are the defined media types (formerly, mime types). The main thing you want to know about media types are that they:

Consist of a type and subtype
The most common types are application, text, audio, image, and multipart
The most common values (type and subtype) are application/json, application/xml, text/html, audio/mpeg, image/png, and multipart/form-data

Query Parameters

The HTTP specification allows for parameters to be added to the URL in form of key=value pairs. Query parameters come after a ? character and are separated by & characters; for example, the following request to a hypothetical API:

GET https://api.example.com/degrees?limit=3&offset=2

passes two query parameters: limit=3 and offset=2. Note that the URL path in the example above is still /degrees; that is, the ? character terminates the URL path, and any characters that follow create the query parameter set for the request.

In REST architectures, query parameters are often used to allow clients to provide additional, optional arguments to the request.

Common uses of query parameters in RESTful APIs include:

Pagination: specifying a specific page of results from a collection
Search terms: filtering the objects within a collection by additional search attributes
Other parameters that might apply to most if not all collections such as an ordering attribute (ascending vs descending)

Specifying Query Parameters in FastAPI

FastAPI allows you to specify query parameters directly in a function signature that has been decorated with a @app decorator. When you declare other function parameters that are not part of the path parameters, they are automatically interpreted as “query” parameters.

For example, consider the following line of Python code:

@app.get('/degrees')
def get_degrees(limit: int):
   #...function implementation...

We are declaring a variable, limit, in the function signature, but it does not appear in the path /degrees being passed to the @app decorator. Thus, FastAPI will consider it to be a query parameter.

Note that, just like any other argument to a Python function, if a default value is not specified in the signature, then the parameter is assumed to be required. We can modify the signature to include a default value – the syntax is exactly the same as with normal functions, e.g.,

@app.get('/degrees')
def get_degrees(limit: int = 10):
   #...function implementation...

With the above signature, the limit query parameter will not be required, and if not passed, will have a default value of 10.

EXERCISE 7

Implement a start query parameter on your GET /degrees endpoint so that the API only returns degrees on or after the year passed in start. The start parameter should be optional, and, it not passed, the API should return the degrees from the very beginning.

Check the behavior by issuing some curl requests in another window, e.g.,

[coe332-vm]$ curl http://api.example.com/degrees?start=1993

Let’s use this idea to update our degrees_api to only return the years starting from the start query parameter year, if that parameter is provided.

Solution

To implement a start query parameter on the GET /degrees endpoint that only returns data for years on or after the start year, we first might write someting like:

@app.get('/degrees')
def degrees(start: int = 1990):
    data = get_data()
    result = []
    # iterate through data and check if years are >= start...

Here, we are specifying a default value of 1990 which happens to be the first year in the datset. Is that a safe approach? Is there a better default value we could use?

In the following solution, we modify the default value to be 0. That way, even if the dataset grows to include more years in the past, the default behavior will still be to return all of the data.

@app.get('/degrees')
def degrees(start: int = 0):
    data = get_data()
    result = []
    for d in data:
        if d['year'] >= start:
            result.append(d)
    return result

Error Handling

What happens if the user enters a non-numeric value for the start parameter? Try it and see what happens:

[coe332-vm]$ curl http://127.0.0.1:8000/degrees?start=abc

Nice! We get a well-formatted JSON object with a fairly descriptive message about what was wrong:

This message is saying the input, abc, of the start query parameter should have been an integer. In other words, FastAPI is automatically taking care of error handling for us! This is one of the biggest benefits to using strong typing in our Python signatures. Much of the error handling, type conversion, etc., can be handled automatically by the underlying library.

We can also inspect the headers that FastAPI set for us. We set -v on our curl command to see those:

[coe332-vm]$ curl -v http://127.0.0.1:8000/degrees?start=abc

> GET /degrees?start=ab HTTP/1.1
> Host: 127.0.0.1:8000
> User-Agent: curl/8.5.0
> Accept: */*
>
< HTTP/1.1 422 Unprocessable Content
< date: Mon, 16 Feb 2026 20:16:53 GMT
< server: uvicorn
< content-length: 150
< content-type: application/json

Indeed, we see that our FastAPI server set a return code of 422, Unprocessable Content. This is very appropriate, as we know the request was a client error.

Returning Non-200 Response Codes

In some cases, the user’s request will satisfy our type requirements but it will still be an invalid request. For example, let’s revisit the GET /degrees/{id} endpoint. Before, we had the following implementation:

@app.get('/degrees/{id}')
def get_degrees_obj(id):
   data = get_data()
   for d in data:
      if d['id'] == id:
            return d
   else:
      return {"message": f"Did not find id {id}"}

But if we inspect the response returned from this enpoint, what status code do we get if the id attribute is an integer but does not correspond to an existing degree?

As before, we use -v to see the details:

[coe332-vm]$ curl -v http://127.0.0.1:8000/degrees/45

> GET /degrees/45 HTTP/1.1
> Host: 127.0.0.1:8000
> User-Agent: curl/8.5.0
> Accept: */*
>
< HTTP/1.1 200 OK
< date: Mon, 16 Feb 2026 20:24:38 GMT
< server: uvicorn
< content-length: 32
< content-type: application/json

Indeed, the 45 passes our type requirements of being an int, but our API doesn’t have a degree object with id. Should this be a 200 “success” response?

In this case, the more appropriate reply would be a 404 “not found” resposne code. FastAPI provides a facility for specifying non-200 status codes through the HTTPException class, a custom Exception class. If you need to review Python’s Exceptions, please see the Unit3 notes on Error Handling.

To use the HTTPException object, we first need to import it from the fastapi package:

from fastapi import HTTPException

Then, as with any other Exception object, we use the raise keyword. The HTTPException constructor takes two arguments, status_code, which should be an integrer, and detail, which should be a message to the client. Here is an updated version of the GET /degrees/{id} endpoint that returns a 404 when the id is not found:

@app.get('/degrees/{id}')
def get_degrees_obj(id):
   data = get_data()
   for d in data:
      if d['id'] == id:
            return d
   else:
      raise HTTPException(status_code=404, detail=f"Did not find id {id}")

EXERCISE 8

Update your GET /degrees/{id} and GET /degrees/{id}/degrees endpoints to return 404 response codes when the id passed does not exist. Use curl or requests to confirm that your server indeed returns a 404.

The Power of Types: Automatically Generated API Docs

We already mentioned that providing types on the parameters of our API endpoints allows FastAPI to automatically validate HTTP requests, return error codes when user’s requests failed to meet our type specification, and perform automatic type conversions when the requests were valid. In addition to these benefits, another powerful aspect is that FastAPI can automatically generate documentation for all of our endpoints based on the types. In fact, FastAPI has already done this for our API and made it available via the /openapi.json endpoint:

[coe332-vm]$ curl localhost:8000/openapi.json | jq

{
"openapi": "3.1.0",
"info": {
   "title": "FastAPI",
   "version": "0.1.0"
},
"paths": {
   "/": {
      "get": {
      "summary": "Root",
      "operationId": "root__get",
      "responses": {
         "200": {
            "description": "Successful Response",
            "content": {
            "application/json": {
               "schema": {}
            }
. . .

It even serves an interactive application for us on the /docs URL. We’ll do more with that later in the semester.

Note

The Linux command-line utility jq is nice for displaying JSON in pretty-print format.

We have created a secure proxy to your VM that will allow you to reach port 8000 through your web browser. There are two points to keep in mind.

First, when running the FastAPI dev server, we need to specify --host 0.0.0.0 to instruct the server to listen on all interfaces. So, for example, the full command would become: fastapi dev --host 0.0.0.0 main.py.
Second, we need to use the base URL associated with our TACC usernames of the form: https://<tacc_username>.coe332-2026.tacc.cloud. For example, since my TACC username is jstubbs, my base URL would be https://jstubbs.coe332-2026.tacc.cloud.

Then, I can navigate to any URL path that my FasAPI server supports. Try navigating to /docs to see the interactive documentation site that is automatically generated for you by FasAPI based on your types.

Try clicking the “Try it out” buttons to exercise your endpoints!

CRUD Operations

To this point, we have looked at only the GET method. There are three other methods that are important to learn when working with REST APIs - PUT, POST, and DELETE. Collectively, these four methods perform CRUD operations on our data:

Create: POST - add a new item to a collection
Read: GET - get an item from a collection
Update: PUT - edit an existing item in a collection
Delete: DELETE - delete an item from a collection

To implement one of these methods in a FastAPI route, we use the @app corresponding to the method; e.g., @app.post, @app.put, etc. Then, the function below the decorator must contain some logic to act according to the method and request.

The DELETE

In some ways, the DELETE is the most straight forward because we (typically) do not require a request message. All we need to know to delete the object is the id, which is specified in the URL path. What should the delete do? It should remove the corresponding object from the Python list. Let’s implement that.

We can delete an item from a list using the list.remove(item) method, but we first need make sure the item is actually in the list. Your first attempt might look like this:

@app.delete('/degrees/{id}')
def delete_degrees_obj(id: int):
   data = get_data()
   for item in data:
      if item["id"] == id:
          data.remove(item)
          return {"message": f"Item {id} deleted."}
   raise HTTPException(status_code=404, detail=f"Did not find id {id}")

This code looks reasonable, but let’s test it out to see if it works. Try deleting a key from the dictionary using a DELETE /degrees/{id} request and then try to get it using a GET /degrees/{id} request. What do you notice?

Note

You can specify the HTTP verb to send using the -X flag to curl. For example, -X DELETE will send a DELETE request.

The item wasn’t deleted! Why is that? It is because the get_data function returns a hard-coded Python list every time it is called. In order to fix this issue, we need to create a global Python object that all of our endpoints can reference.

In order to implement that, we’ll first replace get_data with a globally-defined variable, data, like so:

data = [ {'id': 0, 'year': 1990, 'degrees': 5818},
         {'id': 1, 'year': 1991, 'degrees': 5725},
         {'id': 2, 'year': 1992, 'degrees': 6005},
         {'id': 3, 'year': 1993, 'degrees': 6123},
         {'id': 4, 'year': 1994, 'degrees': 6096} ]

Then, in each API route function, we’ll replace the call to get_data with a reference to global data. For example, our delete_degrees_obj function will become:

@app.delete('/degrees/{id}')
def delete_degrees_obj(id: int):
   global data
   for item in data:
      if item["id"] == id:
          data.remove(item)
          return {"message": f"Item {id} deleted."}
   raise HTTPException(status_code=404, detail=f"Did not find id {id}")

EXERCISE 9

Replace the references to get_data in each of the endpoints: GET /degrees, GET /degrees/{id}, DELETE /degrees/{id}, and GET '/degrees/{id}/degrees'.

The POST and PUT – Modeling Request Messages with Pydantic

In order for the user of our API to describe a new degrees object that they want us to create (the POST method), or an update to an existing degrees object (the PUT method), they need to provide us with a detailed description of the object. Doing so in URL path or query parameters would be unwieldy, so the HTTP specification allows for passing a message in the request body. For our APIs, we’ll specify that these request messages should be formatted as JSON objects. If the API server successfully processes the request and creates or updates the object, then we’ll return a response message containing a description of the object we create or update. This will also be a JSON object.

To keep everything strongly typed, we’ll use Pydantic to model the request and response messages. FastAPI integrates with Pydantic so that we can specify the types of our API endpoints using the models easily.

To begin, we first need to define our Pydantic models. It is common to define a model to represent the requested object and a separate model to represent the object created by the API server and returned in the response. The reason is because often times the API server will add or modify fields provided by the request. In our case, each degrees object has three fields:

id
year
degrees

Should the user who is creating a new degrees object pass the id? How would they know what id value to pass? We likely want to keep the id unique across all degrees objects. How will the user know what the “next” id should be? And even worse, what if two users make requests to create degrees objects at the same time?

It usually makes more sense for the server to supply the (unique) identifier for a resource because it “knows” all of the existing identifiers and can ensure no identifiers are reused. Thus, we’ll have two Pydantic models, one with just year and degrees, representing a user request, and a second that adds an id field, which will be generated by the server. Remember that with Pydantic models, like all Python classes, we can use inheritance to avoid having to repeat the duplicate fields.

from pydantic import BaseModel

class DegreesRequest(BaseModel):
   year: int
   degrees: int

class DegreesResponse(DegreesRequest):
   id: int

With our Pydantic models defined, we are ready to create our POST function. This is the function signature we will use:

@app.post("/degrees")
def create_degrees(d: DegreesRequest) -> DegreesResponse:
   # ...implementation...

Here, we are saying a DegreesRequest object is provided as the POST message body, and a DegreesResponse object is returned. FastAPI automatically takes case of marshaling these objects to and from JSON, and doing validation, etc.

EXERCISE 10

Implement the POST function. Your function should do the follow:

Get the “next” id by looking through the existing data object for the current largest id value and adding 1 to it.
Create a DegreesResponse object using the input DegreesRequest object and the next id computed in 1).
Add the DegreesResponse object to the data object.
Return the DegreesResponse object to the user.

SOLUTION

Here is a complete solution

@app.post("/degrees")
def create_degrees(d: DegreesRequest) -> DegreesResponse:
   global data
   # get the next id
   max_id = 0
   for degrees in data:
      if degrees['id'] > max_id:
            max_id = degrees["id"]
   new_id = max_id + 1
   new_d = DegreesResponse(year=d.year, degrees=d.degrees, id=new_id)
   data.append(new_d.model_dump())
   return new_d

Making POST requests

How do we create POST requests to try out our new endpoint? To make a post request we need to do three things:

Specify the HTTP method is POST.
Send a JSON document as the message associated with the request.
Specify a header, the Content-type header, and give a value of application/json, so that the server knows to interpret the message as a JSON object.

With curl, accomplish each of these as follows:

The HTTP method can be specified with the -X POST flag.
We can use the -d flag to specify the message body. It needs to be formatted as string but contain valid JSON.
We use the -H "Content-type: application/json" to specify the header and its value.

Putting those all together, here is a curl command that works:

curl -H "Content-type: application/json" -X POST -d '{"degrees": 7000, "year": 1995}' localhost:8000/degrees

Advanced FastAPI

Defining the URLs of Our API

EXERCISE 1

EXERCISE 2

Discussion

Typed URL Parameters

EXERCISE 3

Responses in FastAPI

EXERCISE 4

EXERCISE 5

HTTP Content Type Headers

EXERCISE 6

Media Type (or Mime Type)

Query Parameters

Specifying Query Parameters in FastAPI

EXERCISE 7

Solution

Error Handling

Returning Non-200 Response Codes

EXERCISE 8

The Power of Types: Automatically Generated API Docs

CRUD Operations

The DELETE

EXERCISE 9

The POST and PUT – Modeling Request Messages with Pydantic

EXERCISE 10

SOLUTION

Making POST requests

Additional Resources